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dc.contributor.authorHortos, William S.
dc.date.accessioned2017-10-01T18:39:16Z
dc.date.available2017-10-01T18:39:16Z
dc.date.issued2001-08-28
dc.identifier.citationHortos, W. S. (2001). Optimization of real-time protocols for wireless packet-switched, multimedia networks based on partially observed, multivariate point processes. Paper presented at the Proceedings of SPIE - the International Society for Optical Engineering, , 4395 171-187.en_US
dc.identifier.urihttp://hdl.handle.net/11141/1660
dc.descriptionWireless IP networks; real-time protocols; integrated multimedia services; resource allocation; quality-of-service (QoS) routing; multivariate random point processes; adaptive estimation; stochastic optimal control; martingale representations; controlled probability measuresen_US
dc.description.abstractNext-generation wireless networks have been designed to transport integrated multimedia services based on a cellular extension of a packet-switched architecture using variants of the Internet protocol (IP). Each call, arriving to or active within the network, carries demand for one or more services in parallel, where each service type has a guaranteed quality of service (QoS). Admission of new calls to the wireless IP network (WIN) from the gateway of a wired network or from a mobile subscriber (MS) is allowed by call admission control (CAC) procedures. MS roaming among the nodes of the WIN is controlled by handoff procedures between base stations (BSs), or BS controllers (BSCs), and the MSs. Both handoff and CAC procedures are typically embedded in the media access control (MAC) and logical link control (LLC) layers of the WIN protocol stack. Performance metrics, such as, probabilities of call blocking and handoff, control procedures within the WIN protocol. Earlier published results by the author present a method for the performance analysis of wireless multimedia networks based on multivariate point-process (MVPP) models and their semi-martingale representations. The models describe the finite-horizon, transient behavior of the packet flows in integrated multimedia traffic. This paper extends the earlier work to focus on the optimization of real-time control procedures embedded in the WIN protocol stack. The point processes corresponding to the packet flow of each service type and to collateral random network events are decomposed into right-continuous, pure jump processes and predictable, integrated random rate processes. Control of the set of point processes describing WIN behavior is implemented through the construction of an absolutely continuous change of a reference probability measure on network events to a controlled measure. With respect to the constructed controlled measure, the integrated random rates in the semi-martingale representations of the network point processes explicitly depend on the parameters of the protocol mechanisms for packet access, routing, switching, handoff, power control, and other resource allocations. The MVPP control approach via constructed probability measure also supports predictive models of packet flows that incorporate measurement-based estimates of the probability distributions for voice, video, data, and other Internet traffic as well as radio path distortions. Optimization of the performance metrics, represented in terms of the MVPPs and the control parameters of candidate WIN protocols for multimedia services, are discussed for both partial and complete observations of network events. The models are further used to develop optimal, recursive stochastic filters of network state, based on partial or incomplete observations of packet flow dynamics.en_US
dc.language.isoen_USen_US
dc.rightsThis published article is made available in accordance with publishers policy. It may be subject to U.S. copyright law. © (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).en_US
dc.rights.urihttp://spie.org/publications/journals/guidelines-for-authors#Terms_of_Useen_US
dc.titleOptimization of real-time protocols for wireless packet-switched, multimedia networks based on partially observed, multivariate point processesen_US
dc.typeConference Proceedingen_US
dc.identifier.doi10.1117/12.438284


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